mice.impute.cens: Impute left censored data with MICE

In LilithF/doMIsaul: Do Multiple Imputation-Based Semi-Supervised and Unsupervised Learning

Description

Function from Lapidus et al. for imputing left-censored data with mice

Usage

mice.impute.cens(
  y,
  ry,
  x,
  lod.j,
  lod.name = "lod",
  REDRAW = FALSE,
  wy = NULL,
  ...
)

Arguments

y	Vector to be imputed
ry	Logical vector of length length(y) indicating the the subset y[ry] of elements in y to which the imputation model is fitted. The ry generally distinguishes the observed (TRUE) and missing values (FALSE) in y.
x	Numeric design matrix with length(y) rows with predictors for y. Matrix x may have no missing values.
lod.j	censoring value.
lod.name	suffix name used for the censored variable.
REDRAW	Boolean indicating whether values should be redrawn if some are over the censoring limit
wy	Logical vector of length length(y). A TRUE value indicates locations in y for which imputations are created.
...	Other named arguments.

Value

Vector with imputed data, same type as y, and of length sum(wy).

LilithF/doMIsaul documentation built on Dec. 17, 2021, 12:08 a.m.